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🌟 Master when() in Apache Spark & Databricks! 🌟
In this 45-second Q&A, learn how to use the when() function to apply conditional logic in DataFrames in Databricks and Apache Spark.

🔍 What is when()?
The when() function allows you to create conditional expressions, assigning values based on conditions, similar to if-else logic.

📜 Syntax
from pyspark.sql.functions import when
df_result = df.withColumn("new_column", when(condition, value).otherwise(other_value))

💡 Example
Suppose you have a DataFrame, students, with columns name and score.
students = spark.createDataFrame([("Alice", 85), ("Bob", 45)], ["name", "score"])
result = students.withColumn("grade", when(col("score") != 50, "Pass").otherwise("Fail"))
This adds a grade column: Alice gets "Pass", Bob gets "Fail".

🛠️ Tips
Chain multiple when() clauses for complex conditions.
Use otherwise() to handle default cases.
Combine with select() for concise outputs.

📚 Official Documentation
https://spark.apache.org/docs/latest/api/p...

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